NLP-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Multimodal

Multimodal Emotion Recognition

IEMOCAP

The IEMOCAP (Busso et al., 2008) contains the acts of 10 speakers in a two-way conversation segmented into utterances. The medium of the conversations in all the videos is English. The database contains the following categorical labels: anger, happiness, sadness, neutral, excitement, frustration, fear, surprise, and other.

Multimodal Sentiment Analysis

MOSI

The MOSI dataset (Zadeh et al., 2016) is a dataset rich in sentimental expressions where 93 people review topics in English. The videos are segmented with each segments sentiment label scored between +3 (strong positive) to -3 (strong negative) by 5 annotators.